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通过肌肉成像评估的GNE肌病中的上身受累情况。

Upper body involvement in GNE myopathy assessed by muscle imaging.

作者信息

Torchia E, Lucchini M, Bortolani S, Monforte M, Garibaldi M, Mirabella M, Tartaglione T, Ricci E, Tasca G

机构信息

Università Cattolica del Sacro Cuore, Rome, Italy.

Università Cattolica del Sacro Cuore, Rome, Italy; UOC di Neurologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.

出版信息

Neuromuscul Disord. 2022 May;32(5):410-418. doi: 10.1016/j.nmd.2021.12.007. Epub 2022 Jan 12.

Abstract

Upper body muscle involvement has never been systematically investigated in GNE myopathy (GNEM). Aims of our study were to explore upper body involvement in GNEM patients by means of muscle MRI, to compare the degree of pathology with that of lower body and to validate the MRI pattern of the lower limbs in novel patients. MRI scans of 9 GNEM patients were retrospectively evaluated. T1-weighted and short-tau inversion recovery images were scored. As a result, serratus anterior was involved in all patients, followed by subscapularis and trapezius muscles. The majority of scans consistently showed hypotrophy of pectoralis minor. Conversely, cranial muscles including the tongue were always spared while pectoralis major and latissimus dorsi were relatively spared. We confirmed the known pattern of involvement in the pelvic girdle and limbs, that were more significantly affected than the upper girdle in all disease stages. Paraspinal muscles were also frequently affected displaying both a cranio-caudal and latero-medial gradient of severity along the body axis. Upper girdle MRI highlights a selective muscle involvement in GNEM, offering an added value in patients' diagnostic workup and deep stratification.

摘要

上肢肌肉受累情况在GNE肌病(GNEM)中从未得到系统研究。我们研究的目的是通过肌肉MRI探索GNEM患者的上肢受累情况,将病理程度与下肢进行比较,并在新患者中验证下肢的MRI模式。对9例GNEM患者的MRI扫描进行回顾性评估。对T1加权和短tau反转恢复图像进行评分。结果显示,所有患者的前锯肌均受累,其次是肩胛下肌和斜方肌。大多数扫描结果一致显示胸小肌萎缩。相反,包括舌肌在内的颅部肌肉始终未受累,而胸大肌和背阔肌相对未受累。我们证实了骨盆带和四肢已知的受累模式,在所有疾病阶段,它们比上半身受影响更显著。椎旁肌也经常受累,沿身体轴线显示出从头到尾和从外侧到内侧的严重程度梯度。上肢带MRI突出显示了GNEM中肌肉的选择性受累,为患者的诊断检查和深度分层提供了附加价值。

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